Thesis Type: Postgraduate
Institution Of The Thesis: Middle East Technical University, Graduate School of Natural and Applied Sciences, Turkey
Approval Date: 2019
Thesis Language: English
Student: GÖRKEM NARİN
Principal Supervisor (For Co-Supervisor Theses): Seyit Sencer Koç
Co-Supervisor: Çağatay CandanAbstract:
Detection of slow moving targets with small radar cross sections (RCS) is a challenging problem for the Ground Moving Target Indication (GMTI) systems. GMTI systems face high false alarm and/or frequent target miss rates for such targets. Synthetic Aperture Radar (SAR) systems, on the other hand, offer sufficiently large target energy return, unfortunately not localized to a point in the SAR image due to target motion. This thesis is focused on the study of two methods for moving target detection in SAR images via processing the unlocalized target signature. The first method uses the effect of the target motion parameters on the target signature. This method aims to focus the unlocalized moving target signature in the SAR image by estimating motion parameters. The results are presented via a point target spotlight SAR imaging simulator developed within the scope of this thesis. Secondly, a novel dynamic programming based approach is presented to detect slow moving targets. Contrary to the former one, this method does not require target motion parameters; instead, it captures the unlocalized signatures in the SAR image by using real-valued reflectivity amplitudes of the image. The performance of the method is illustrated with simulated and field data containing multiple slow moving targets.